Overcoming limitations to maximise the impact of AI
Summary
This roundtable collects views from senior iGaming executives on the realistic limits and practical opportunities of AI in the industry. Contributors — including leaders from BetGames, Playson, OpenSlots and The Mill Adventure — stress that AI’s benefits hinge on high-quality data, appropriate use-cases, cost-effective infrastructure and clear governance. While AI can speed development, personalise entertainment and strengthen security, it will not magic away fraud or governance shortcomings; instead the industry must prepare through training, partnerships and transparent regulation.
Key Points
- Data quality and access are the foundation for any effective AI deployment; poor input data produces poor outputs.
- Market readiness is limited — many operators and studios lack the talent and processes to extract AI value today.
- Infrastructure and cost are material constraints; scaling AI requires balancing performance with sustainable spend or partnering with specialists.
- Player trust and transparency are critical — independent certification and open communication about AI use will help maintain confidence.
- AI should be applied where it adds measurable value (faster prototyping, personalised content, fraud detection), not used for its own sake.
- Fraud will persist and may be amplified by AI; training staff to use AI properly is essential to manage risks.
- Partnerships and two-way, privacy-safe data sharing between studios and tech providers will unlock better personalisation and faster innovation.
- Emerging trends such as “vibe coding” and on-demand reskinning could change slot production models within 6–24 months.
- Governance, compliance and alignment with regulators must accompany technical rollouts to ensure fairness and player protection.
Content summary
The article is a Q&A-style roundtable where executives highlight the practical limits of AI in iGaming and outline how to get the most from it. Key themes: AI is data-hungry and reliant on clean, current datasets; suppliers without direct player data face personalisation limits; infrastructure will become commoditised but costs and scaling remain pressing issues; and player trust and regulatory clarity are prerequisites for broad adoption.
Speakers emphasise selective adoption — using AI to accelerate development and prototyping, improve player experiences, and augment fraud and AML detection — while warning it’s not a panacea. They recommend realistic deployment plans: partner where it makes sense, invest in staff training, maintain and curate knowledge bases, and pursue certification and transparent governance to avoid unintended unfairness.
Context and relevance
This piece sits at the intersection of product, compliance and technology in iGaming. As GenAI tools mature, the industry faces both opportunity and exposure: more personalised player journeys and faster content iteration on one hand, and heightened fraud, cost pressures and regulatory scrutiny on the other. For operators, suppliers and regulators, the article highlights why strategic data practices, partnerships and governance are urgent priorities.
Why should I read this?
Look — if you work in iGaming and you haven’t got five minutes to see where AI actually helps (and where it bites back), read this. It’s a reality check from people building games, ops and platforms: don’t chase shiny tools, sort data, train people, partner smartly and keep regulators in the loop. Saves you time and helps you avoid costly mistakes.
Author style
Punchy — the contributors are blunt and practical. If you’re responsible for product, tech or compliance, treat this as a short brief that amplifies how important the details are: data hygiene, governance and targeted use-cases matter more than hype.
Source
Source: https://igamingexpert.com/features/ai-eradicate-ongoing-challenges/
